Cloud computing architecture for Tagging Arabic Text Using Hybrid Model

Part of speech (POS) is one of the primary methods employed to develop any language corpus. Each language consists of several tags applied in different applications, such as natural language processing (NLP), speech synthesis, and information extraction.  One of the main benefits of adopting cloud computing services is the offer a low cost and time to store your company data compared to traditional methods. This paper presents and deploys a cloud computing architecture for Tagging Arabic text using a hybrid model, which will help reduce the efforts and cost. The results show an excellent accuracy rate in tagging an Arabic text and quickly respond. Previous studies are compared based on relevant rating factors, which achieved high accuracy, procession, and recall rate of more than 95%.  The cloud computing tagger attained an accuracy of 99.2%.